Methods and devices for guiding a patient

ABSTRACT

Methods and systems for guiding a patient for a medical examination using a medical apparatus. For example, a computer-implemented method for guiding a patient for a medical examination using a medical apparatus includes: receiving an examination protocol for the medical apparatus; determining a reference position based at least in part on the examination protocol; acquiring a patient position; determining a deviation metric based at least in part on comparing the patient position and the reference position; determining whether the deviation metric is greater than a pre-determined deviation threshold; and if the deviation metric is greater than a pre-determined deviation threshold: generating a positioning guidance based at least in part on the determined deviation metric, the positioning guidance including guidance for positioning the patient relative to the medical apparatus.

1.BACKGROUND OF THE INVENTION

Certain embodiments of the present invention are directed to imageprocessing. More particularly, some embodiments of the invention providemethods and devices for medical image processing. Merely by way ofexample, some embodiments of the invention have been applied to guidinga patient for a medical examination using a medical apparatus. But itwould be recognized that the invention has a much broader range ofapplicability.

Patient positioning during a medical imaging scan is a complex problem.Conventionally, there are hundreds of combinations of standard posescorresponding to various types of scans (e.g., CT, MR, X-ray, PET, etc.)as well as various scanning protocols. It is often difficult for apatient to perform or pose the standard pose during a scan, especiallyfor an injured or elderly patient. Additionally, it is challenging for amedical staff (e.g., a scan technician), who in conventional clinicalpractice often help positions the patient, to visually judge thepositioning correctness of the patient's pose in respect to the standardpose. In particularly, it is especially difficult for scans involving atrauma patient or patient with additional medical equipment oraccessories coupled to the patient's body. At least owing to thechallenges described, medical imaging scans often produce images withunsatisfactory image quality insufficient for diagnosis. As a result,rescans are often performed, leading to reduction in efficiency. It istherefore desirable to have a method or system for patient positioningfor reducing patient positioning errors, improving scanning efficiency,reducing technician workload, and improving scanned image quality forbetter diagnosis.

2. BRIEF SUMMARY OF THE INVENTION

Certain embodiments of the present invention are directed to imageprocessing. More particularly, some embodiments of the invention providemethods and devices for medical image processing. Merely by way ofexample, some embodiments of the invention have been applied to guidinga patient for a medical examination using a medical apparatus. But itwould be recognized that the invention has a much broader range ofapplicability.

In various embodiments, a computer-implemented method for guiding apatient for a medical examination using a medical apparatus includes:receiving an examination protocol for the medical apparatus; determininga reference position based at least in part on the examination protocol;acquiring a patient position; determining a deviation metric based atleast in part on comparing the patient position and the referenceposition; determining whether the deviation metric is greater than apre-determined deviation threshold; and if the deviation metric isgreater than a pre-determined deviation threshold: generating apositioning guidance based at least in part on the determined deviationmetric, the positioning guidance including guidance for positioning thepatient relative to the medical apparatus.

In various embodiments, a system for guiding a patient for a medicalexamination using a medical apparatus includes: a protocol receivingmodule configured to receive an examination protocol for the medicalapparatus; a reference position determining module configured todetermine a reference position based at least in part on the examinationprotocol; a patient position acquiring module configured to acquire apatient position; a deviation metric determining module configured todetermine a deviation metric based at least in part on comparing thepatient position and the reference position; a positioning guidancemodule configured to: determine whether the deviation metric is greaterthan a pre-determined deviation threshold; and if the deviation metricis greater than a pre-determined deviation threshold: generate apositioning guidance based at least in part on the determined deviationmetric. In certain examples, the positioning guidance including guidancefor positioning the patient relative to the medical apparatus. Incertain examples, the patient position acquiring module is furtherconfigured to acquire a second patient position.

In various embodiments, a non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe processes including: receiving an examination protocol for themedical apparatus; determining a reference position based at least inpart on the examination protocol; acquiring a patient position;determining a deviation metric based at least in part on comparing thepatient position and the reference position; determining whether thedeviation metric is greater than a pre-determined deviation threshold;and if the deviation metric is greater than a pre-determined deviationthreshold: generating a positioning guidance based at least in part onthe determined deviation metric, the positioning guidance includingguidance for positioning the patient relative to the medical apparatus.

Depending upon embodiment, one or more benefits may be achieved. Thesebenefits and various additional objects, features and advantages of thepresent invention can be fully appreciated with reference to thedetailed description and accompanying drawings that follow.

3. BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified diagram showing a system for guiding a patientfor a medical examination using a medical apparatus, according to someembodiments of the present invention.

FIG. 2 is a simplified diagram showing a method for guiding a patientfor a medical examination using a medical apparatus, according to someembodiments of the present invention.

FIG. 3 is a simplified diagram showing a computing system, according tosome embodiments of the present invention.

FIG. 4 is a simplified diagram showing a neural network, according tosome embodiments of the present invention.

4. DETAILED DESCRIPTION OF THE INVENTION

Certain embodiments of the present invention are directed to imageprocessing. More particularly, some embodiments of the invention providemethods and devices for medical image processing. Merely by way ofexample, some embodiments of the invention have been applied to guidinga patient for a medical examination using a medical apparatus. But itwould be recognized that the invention has a much broader range ofapplicability.

FIG. 1 is a simplified diagram showing a system for guiding a patientfor a medical examination using a medical apparatus, according to someembodiments of the present invention. This diagram is merely an example,which should not unduly limit the scope of the claims. One of ordinaryskill in the art would recognize many variations, alternatives, andmodifications. In some examples, the system 10 includes a protocolreceiving module 12, a reference position determining module 14, apatient position acquiring module 16, a deviation metric determiningmodule 18, and/or a positioning guidance module 20. In certain examples,the system 10 further includes a foreign object module 22, a signalingmodule 24, a settings module 26, and/or an accessory module 28. In someexamples, the system 10 is a patient position guidance system configuredto guide a patient towards a target position (e.g., a reference positionsuch as a standardized position), such as for medical image acquisition(e.g., an X-ray scan), surgical procedures, patient care, and/orphysical therapy. Although the above has been shown using a selectedgroup of components, there can be many alternatives, modifications, andvariations. For example, some of the components may be expanded and/orcombined. Other components may be inserted to those noted above.Depending upon the embodiment, the arrangement of components may beinterchanged with others replaced.

In various embodiments, the protocol receiving module 12 is configuredto receive an examination protocol, such as an examination protocol forthe medical apparatus. In some examples, the examination protocol isselected by a user. For example, the examination protocol can beselected by a use from a menu, such as a drop-down menu. In certainexamples, the examination protocol corresponds to one or more parametersof the medical apparatus. In various examples, the examination protocolis a scanning protocol.

In various embodiments, the reference position determining module 14 isconfigured to determine a reference position based at least in part onthe examination protocol. In some examples, the reference position is astandard position corresponding to the examination protocol. In certainexamples, the reference position determining module 14 is configured toautomatically determine the reference position. In various examples, thereference position determining module 14 is configured to determine thereference position based at least in part on patient information such aspatient gender, age, and/or measurements. In some examples, thereference position is a template position corresponding to a standardpose, which may correspond to an examination protocol.

In various embodiments, the patient position acquiring module 16 isconfigured to acquire a first patient position. In some examples, thefirst patient position corresponds to a patient position of a patientbefore the patient is adjusted according to a positioning guidance. Incertain examples, the patient position acquiring module 16 is furtherconfigured to acquire a second patient position. In some examples, thesecond patient position corresponds to a patient position of the patientafter the patient is adjusted according to the positioning guidance. Invarious examples, the patient position acquiring module 16 is configuredto acquire a first patient image and generate the first patient positionbased at least in part on the first patient image. In some examples, thepatient position acquiring module 16 is configured to acquire the firstpatient image using a sensor. In certain examples, the sensor includes aRGB sensor, a RGBD sensor, a laser sensor, a FIR sensor, a NIR sensor,and/or a lidar sensor. In some examples, the sensor includes a pluralityof sensors, such as arranged as a sensor array.

In various embodiments, the patient position acquiring module 16 isconfigured to generate the first patient position based at least in parton the first patient image using a feature extraction model (e.g., aneural network trained for extracting one or more features). In certainembodiments, the patient position acquiring module 16 is configured todetermine one or more internal landmarks associated with the acquiredfirst patient image. In some examples, the one or more internallandmarks includes an anatomical feature (e.g., a rib or a joint). Insome embodiments, the patient position acquiring module 16 is furtherconfigured to determine one or more external landmarks associated withthe acquired first patient image. In certain examples, the one or moreexternal landmarks includes a non-anatomical object (e.g., a medicalreference accessory). In various embodiments, the patient positionacquiring module 16 is configured to generate a first patientrepresentation. In certain examples, the first patient representation istwo-dimensional or three-dimensional. In some examples, the patientrepresentation includes an image, a kinematic model, a skeleton model, asurface model, a mesh model, a point cloud, and/or a feature listincluding one or more features each having a corresponding coordinate(e.g., within a scan volume of the scanning apparatus). In someexamples, the patient acquiring module 16 is configured to generatepatient representation using a neural network (e.g., a convolutionalneural network), such as a neural network trained for generating patientrepresentation. In certain examples, the neural network trained forgenerating patient representation is the same neural network trained forextracting one or more features.

In various embodiments, the deviation metric determining module 18 isconfigured to determine a first deviation metric. For example, thedeviation metric determining module 18 is configured to determine thefirst deviation metric based at least in part on the first patientposition (e.g., position before adjustment according to a positioningguidance) and the reference position (e.g., standard position accordingto an examination protocol). For example, the deviation metricdetermining module 18 is configured to determine the first deviationmetric based at least in part on comparing (e.g., determining adifference between) the first patient position and the referenceposition. In various examples, the first deviation metric is a score, amatrix, or a vector. In some embodiments, the deviation metricdetermining module 18 is configured to determine a second deviationmetric. For example, the deviation metric determining module 18 isconfigured to determine the second deviation metric based at least inpart on the second patient position (e.g., position after adjustmentaccording to a positioning guidance) and the reference position (e.g.,standard position according to an examination protocol). For example,the deviation metric determining module 18 is configured to determinethe second deviation metric based at least in part on comparing (e.g.,determining a difference between) the second patient position and thereference position. In various examples, the second deviation metric isa score, a matrix, or a vector.

In certain embodiments, the deviation metric determining module 18 isconfigured to determine a reference vector based at least in part on thereference position, determine a first patient vector based at least inpart on the first patient position, determine a first deviation vectorbased at least in part on the reference vector and the first patientvector, and determine the first deviation metric based at least in parton the first deviation vector. As an example, the deviation metricdetermining module 18 is configured to determine a distance (e.g.,Euclidean distance) between the first patient vector and the referencevector and determine the deviation metric and/or a similarity metricbased at least in part on the determined distance (e.g., Euclideandistance). In various embodiments, the deviation metric determiningmodule 18 is configured to determine one or more anatomical features.For example, the determined one or more anatomical features isassociated with (e.g., pertinent to) the medical examination.

In various examples, the deviation metric determining module 18 isconfigured to classify the first deviation vector as irrelevant if thefirst deviation vector is determined based on an anatomical feature thatis not included in the one or more anatomical features, and classify thefirst deviation vector as relevant if the first deviation vector isdetermined based on an anatomical feature that is included in the one ormore anatomical features. For example, for a fractured rib examination,the deviation metric determining module 18 is configured to classify anarm deviation vector determined based on the arm (e.g., an arm vectorand a reference arm vector) to be irrelevant, whereas the deviationmetric determining module 18 is configured to classify a rib-deviationvector determined based on the rib (e.g., a rib vector and a referencerib vector) to be relevant. In some examples, a deviation metriccorresponds to a similarity metric (e.g., a similarity score). Incertain examples, the deviation metric determining module 18 isconfigured to determine a deviation metric based on part of a patientbody.

In various embodiments, the positioning guidance module 20 is configuredto determine whether the first deviation metric is greater than apre-determined deviation threshold. For example, the pre-determineddeviation threshold is selected by a user, such as via a menu. In someexamples, the positioning guidance module 20 is further configured to,if the first deviation metric is determined to be greater than (e.g.,corresponding to a dissatisfactory patient position) a pre-determineddeviation threshold, generate a first positioning guidance based atleast in part on the determined first deviation metric. In certainexamples, the first positioning guidance includes guidance forpositioning the patient relative to the medical apparatus. In someexamples, the first positioning guidance includes guidance for thepatient or a medical staff to adjust the patient or the medicalapparatus (e.g., an X-ray tube). In certain examples, the positioningguidance module 20 is configured to determine whether the seconddeviation metric is greater than (e.g., corresponding to adissatisfactory patient position) the pre-determined deviationthreshold. In some examples, a positioning guidance includes guidancefor adjusting the patient from the patient position towards (e.g., tofit) the reference position, such as until the deviation between anadjusted position of the adjusted patient and the reference position islesser than a predetermined acceptable deviation level.

In some embodiments, the positioning guidance module 20 is configured topresent the first positioning guidance continuously, such as to presentthe first positioning guidance live with real-time or near real-timeupdate. In certain examples, the positioning guidance module 20 isconfigured to present the first positioning guidance statically, such asto present the first positioning guidance as fixed. In various examples,the positioning guidance module 20 is configured to generate a visualguidance and/or an audio guidance. In some embodiments, the positioningguidance module 20 is configured to generate, as the visual guidance, avisual representation on a display screen, a hologram in thethree-dimensional space, a two-dimensional projection from a projector,an augmented reality representation in an augmented reality eyewear, avirtual reality representation in a virtual reality eyewear, and/or alighting cue indicated by a light-emitting device. In certain examples,the positioning guidance module 20 is configured to generate the audioguidance (e.g., via a speaker) having an audio volume corresponding to amagnitude of the deviation metric. In some examples, the positioningguidance module 20 is configured to generate an overlay highlighting thefirst deviation metric associated with the first patient position andthe reference position. In various examples, the positioning guidancemodule 20 is configured to present the overlay overlaid onto the firstpatient position or the first patient image. In certain examples, thepositioning guidance module 20 is configured to present the referenceposition for guiding the positioning of the patient.

In some embodiments, the foreign object module 22 is configured todetect a foreign object based at least in part on the acquired firstpatient image. For example, the foreign object includes a blockingobject that can block the medical apparatus from following a pathaccording to a protocol, an opaque (e.g., radiation-opaque) object tothe medical apparatus (e.g., an X-ray scanner) that can block pertinentanatomical features, and/or an interfering (e.g., radiation-interfering)object which can lead to poor image quality. In various examples, theforeign object module 22 is configured to generate a collision avoidancebased at least in part on the foreign object, such as to generate acollision avoidance based at least in part on the location and/or thedimensions of the foreign object (e.g., a device, a part of the patient,a part of a medical staff). In certain examples, the collision avoidanceincludes a pause scan instruction, a stop scan instruction, an audioalert, a visual alert, and an/or overriding re-routing scan path (e.g.,a path avoiding collision with the foreign object).

In some embodiments, the signaling module 24 is configured to generate asignal for indicating that the patient is ready for examination (e.g.,medical examination), such as if the first deviation metric is smallerthan or equal to (e.g., corresponding to a satisfactory patientposition) the pre-determined deviation threshold. In various examples,the signaling module 24 is configured to generate a signal forindicating that the patient is ready for examination using anexamination setting. In certain examples, the signal for indicating thatthe patient is ready for examination includes a visual signal and/or anaudio signal. In some examples, the signaling module 24 is furtherconfigured to present the signal for indicating that the patient isready, such as via a display, such as via a user interface.

In some embodiments, the settings module 26 is configured to determinethe examination setting. In certain examples, the examination settingincludes a scanning path, a scanning angulation, a scanning parameter, ascanning speed, a scanning dose, and/or patient information. In certainexamples, the settings module 26 is further configured to determine theexamination setting in real-time based at least in part on the referenceposition and/or the first patient position. In some examples, thesettings module 26 is configured to select the examination setting froma plurality of pre-determined examination settings.

In some embodiments, the accessory module 28 is configured to determinea reference accessory position, acquire a first accessory position, anddetermine a first accessory deviation metric based at least in part onthe first accessory position and the reference accessory position. Incertain examples, the accessory module 28 includes and/or controls aprotocol receiving module (e.g., protocol receiving module 12), areference position determining module (e.g., reference positiondetermining module 14), a patient position acquiring module (e.g.,patient position acquiring module 16), a deviation metric determiningmodule (e.g., deviation metric determining module 18), and/or apositioning guidance module (e.g., positioning guidance module 20). Invarious examples, the accessory module 28 is configured to determine thefirst accessory deviation metric based at least in part on comparing(e.g., determining a difference between) the first accessory positionand the reference accessory position. In various examples, the accessorymodule 28 is configured to determine whether the first accessorydeviation metric is greater than a pre-determined accessory deviationthreshold. The pre-determined accessory deviation threshold may beselected by a user, such as via a menu.

In some examples, the accessory module 28 is configured to, if the firstaccessory deviation metric is greater than a pre-determined accessorydeviation threshold, generate a first accessory positioning guidancebased at least in part on the determined first accessory deviationmetric. In some examples, the first accessory positioning guidanceincludes guidance for positioning the patient relative to the accessory.In some examples, the accessory module 28 is configured to acquire asecond accessory position and determine a second accessory deviationmetric based at least in part on the second accessory position and thereference accessory position. For example, the accessory module 28 isconfigured to determine the second accessory deviation metric based atleast in part on comparing (e.g., determining a difference between) thesecond accessory position and the reference accessory position. anddetermine whether the second accessory deviation metric is greater thanthe pre-determined accessory deviation threshold. In various examples,the first accessory position corresponds to a position of an accessory(e.g., a medical accessory, such as a coil) before adjustment (e.g.,according to the accessory positioning guidance), whereas the secondaccessory position corresponds to a position of the accessory afteradjustment.

FIG. 2 is a simplified diagram showing a method for guiding a patientfor a medical examination using a medical apparatus, according to someembodiments of the present invention. This diagram is merely an example,which should not unduly limit the scope of the claims. One of ordinaryskill in the art would recognize many variations, alternatives, andmodifications. In some examples, the method S100 includes a process S102of receiving an examination protocol for a medical apparatus, a processS104 of determining a reference position based at least in part on theexamination protocol, a process S106 of acquiring a patient position, aprocess S108 of determining a deviation metric based at least in part oncomparing the patient position and the reference position, a processS110 of determining whether the deviation metric is greater than apre-determined deviation threshold, a process S112 of generating asignal for indicating the patient is ready for the medical examinationif the deviation metric is not greater than the pre-determined deviationthreshold, and/or a process S114 of generating a positioning guidancebased at least in part on the determined deviation metric. In certainexamples, one or more processes of the method S100 is repeated, such asafter the patient and/or the medical apparatus is adjusted according tothe positioning guidance. For example, the process S106, S108, and S110are repeated after each patient adjustment. Although the above has beenshown using a selected group of processes for the method, there can bemany alternatives, modifications, and variations. For example, some ofthe processes may be expanded and/or combined. Other processes may beinserted to those noted above. Depending upon the embodiment, thesequence of processes may be interchanged with others replaced.

In some embodiments, the process S102 of receiving an examinationprotocol for a medical apparatus includes receiving an examinationprotocol selected by a user (e.g., a medical staff, a specialist, aphysician), such as via a menu (e.g., a drop-down menu). In certainexamples, the process S102 of receiving an examination protocol includesreceiving the examination protocol selected from a plurality ofpre-determined examination protocols. In various examples, the processS102 of receiving an examination protocol includes receiving theexamination protocol generated by a trained protocol-generating model(e.g., a neural network). In some examples, the trainedprotocol-generating model is configured to generate the examinationprotocol based at least in part on patient information (e.g., medicalcondition, physical condition, and/or measurements), medical examinationtype, and/or target examination body part.

In some embodiments, the process S104 of determining a referenceposition based at least in part on the examination protocol includesdetermining the reference position based at least in part on one or moreparameters corresponding to the examination protocol. In some examples,the process S104 of determining a reference position includesdetermining the reference position based at least in part on patientinformation (e.g., medical condition, physical condition, and/ormeasurements). In various examples, the process S104 of determining areference position includes selecting the reference position from aplurality of pre-determined reference positions.

In some embodiments, the process S106 of acquiring a patient positionincludes acquiring a patient image and generating the patient positionbased at least in part on the patient image. In certain examples,acquiring the patient image includes acquiring the patient image using asensor, such as a RGB sensor, a RGBD sensor, a laser sensor, a FIRsensor, a NIR sensor, and a lidar sensor. In various examples,generating the patient position based at least in part on the acquiredpatient image includes determining one or more internal landmarksassociated with the acquired patient image. In some examples, the one ormore internal landmarks includes one or more anatomical features. Incertain examples, generating the patient position based at least in parton the acquired patient image includes determining one or more externallandmarks associated with the acquired patient image. In some examples,the one or more external landmarks includes one or more non-anatomicalobjects.

In certain examples, generating the patient position based at least inpart on the acquired patient image includes generating a patientrepresentation. In certain examples, the first patient representation istwo-dimensional or three-dimensional. In certain examples, the patientrepresentation includes an image, a kinematic model, a skeleton model, asurface model, a mesh model, a point cloud, and/or a feature listincluding one or more features each having a corresponding coordinate.In various examples, the patient representation includes a parameterizedhuman model. In some embodiments, the process S106 of acquiring apatient position is repeated after each time the patient position isadjusted (e.g., adjusted according to a patient positioning guidance).

In some embodiments, the process S108 of determining a deviation metricbased at least in part on comparing the patient position and thereference position includes determining a reference vector based atleast in part on the determined reference position, determining apatient vector based at least in part on the acquired patient position,determining a deviation vector based at least in part on the referencevector and the patient vector, and determining the deviation metricbased at least in part on the deviation vector. In certain embodiments,determining the deviation metric includes receiving one or moreanatomical features associated with the medical examination. In variousexamples, determining the deviation metric includes classifying thedeviation vector as irrelevant if the deviation vector is determinedbased on an anatomical feature that is not included in the one or moreanatomical features. In certain examples, determining the deviationmetric includes classifying the deviation vector as relevant if thedeviation vector is determined based on an anatomical feature that isincluded in the one or more anatomical features. In some embodiments,the process S108 of determining a deviation metric is repeated aftereach time the process S106 of acquiring a patient position is repeated,such as after each time the patient position is adjusted (e.g., adjustedaccording to a patient positioning guidance).

In some embodiments, the process S110 of determining whether thedeviation metric is greater than a pre-determined deviation thresholdincludes selecting the pre-determined deviation threshold, such as via amenu. In other embodiments, the process S110 of determining whether thedeviation metric is greater than a pre-determined deviation thresholdincludes determining whether the deviation metric is greater than orequal to the pre-determined deviation threshold. In some examples, theprocess S110 of determining whether the deviation metric is greater thana pre-determined deviation threshold includes comparing the deviationmetric with one or more pre-determined deviation thresholds.

In some embodiments, the process S112 of generating a signal forindicating the patient is ready for the medical examination includesgenerating a signal for indicating that the patient is ready for themedical examination using an examination setting. In certain examples,the process S112 is performed if the deviation metric is not greaterthan the pre-determined deviation threshold.

In some embodiments, the process S114 of generating a positioningguidance based at least in part on the determined deviation metricincludes generating a positioning guidance based at least in part on thedetermined deviation metric. In some examples, the positioning guidanceincludes guidance for positioning the patient relative to the medicalapparatus. In some examples, generating the positioning guidanceincludes generating a visual guidance and/or an audio guidance. Incertain examples, generating the visual guidance includes generating avisual representation on a display screen, a hologram in thethree-dimensional space, a two-dimensional projection from a projector,an augmented reality representation in an augmented reality eyewear, avirtual reality representation in a virtual reality eyewear, and/or alighting cue indicated by a light-emitting device. In various examples,generating the audio guidance includes generating an audio guidancehaving an audio volume corresponding to a magnitude of the deviationmetric. In certain examples, generating the visual guidance includesgenerating an overlay highlighting the deviation metric associated withthe acquired patient position (e.g., position before adjustment) and thereference position. For example, the overlay highlights showingdifferences between the acquired patient position and the referenceposition. In some examples, the method S100 further includes presentingthe reference position for guiding the positioning of the patient. Forexample, the process S114 of generating a positioning guidance includespresenting the reference position. In certain examples, the process S114is performed if the deviation metric is greater than or equal to thepre-determined deviation threshold.

In certain embodiments, the method S100 further includes detecting aforeign object based at least in part on an acquired patient image,generating a collision avoidance based at least in part on the foreignobject. In certain examples, the generating the collision avoidanceincludes generating the collision avoidance based at least in part onthe location and/or the dimensions of the foreign object. In certainexamples, the collision avoidance includes a pause scan instruction, astop scan instruction, an audio alert, a visual alert, and/or anoverriding re-routing scan path (e.g., a path avoiding collision withthe foreign object). In various examples, the detecting a foreign objectis performed before and/or during the imaging (e.g., as part of themedical examination) of a patient, such as after a signal for indicatingthe patient is ready for the medical examination is generated.

In certain embodiments, the method S100 further includes determining theexamination setting, the examination setting including a scanning path,a scanning angulation, a scanning parameter, a scanning speed, ascanning dose, and/or patient information. In certain examples,determining the examination setting includes determining the examinationsetting in real-time based at least in part on the reference positionand/or the patient position. In various examples, determining theexamination setting includes selecting the examination setting from aplurality of pre-determined examination settings.

In certain embodiments, the method S100 further includes presenting thepositioning guidance continuously, such as presenting the positioningguidance live with real-time or near real-time update. In certainexamples, the method S100 further includes presenting the positioningguidance statically, such as presenting the positioning guidance asfixed, such as until being updated with a new positioning guidancegenerated once the patient is adjusted and a new deviation metric isgenerated based on a newly acquired patient position.

In certain embodiments, the method S100 further includes determining areference accessory position, acquiring an accessory position,determining an accessory deviation metric based at least in part oncomparing the accessory position and the reference accessory position,and determining whether the accessory deviation metric is greater than apre-determined accessory deviation threshold. In various examples, themethod further includes generating a signal for indicating the accessoryis in position for the medical examination if the deviation metric isnot greater than the pre-determined deviation threshold and/orgenerating an accessory positioning guidance based at least in part onthe determined accessory deviation metric if the first accessorydeviation metric is greater than a pre-determined accessory deviationthreshold. In various examples, the accessory positioning guidanceincludes guidance for positioning the patient relative to the accessory.In certain examples, determining a reference position, acquiring anaccessory position, determining an accessory deviation metric, and/ordetermining whether the accessory deviation metric is greater than thepre-determined accessory deviation threshold is repeated, such as afterthe accessory and/or the medical apparatus is adjusted according to theaccessory positioning guidance.

FIG. 3 is a simplified diagram showing a computing system, according tosome embodiments. This diagram is merely an example, which should notunduly limit the scope of the claims. One of ordinary skill in the artwould recognize many variations, alternatives, and modifications. Incertain examples, the computing system 6000 is a general-purposecomputing device. In some examples, the computing system 6000 includesone or more processing units 6002 (e.g., one or more processors), one ormore system memories 6004, one or more buses 6006, one or moreinput/output (I/O) interfaces 6008, and/or one or more network adapters6012. In certain examples, the one or more buses 6006 connect varioussystem components including, for example, the one or more systemmemories 6004, the one or more processing units 6002, the one or moreinput/output (I/O) interfaces 6008, and/or the one or more networkadapters 6012. Although the above has been shown using a selected groupof components for the computing system, there can be many alternatives,modifications, and variations. For example, some of the components maybe expanded and/or combined. Other components may be inserted to thosenoted above. Depending upon the embodiment, the arrangement ofcomponents may be interchanged with others replaced.

In certain examples, the computing system 6000 is a computer (e.g., aserver computer, a client computer), a smartphone, a tablet, or awearable device. In some examples, some or all processes (e.g., steps)of the method S100 are performed by the computing system 6000. Incertain examples, some or all processes (e.g., steps) of the method S100are performed by the one or more processing units 6002 directed by oneor more codes. For example, the one or more codes are stored in the oneor more system memories 6004 (e.g., one or more non-transitorycomputer-readable media), and are readable by the computing system 6000(e.g., readable by the one or more processing units 6002). In variousexamples, the one or more system memories 6004 include one or morecomputer-readable media in the form of volatile memory, such as arandom-access memory (RAM) 6014, a cache memory 6016, and/or a storagesystem 6018 (e.g., a floppy disk, a CD-ROM, and/or a DVD-ROM).

In some examples, the one or more input/output (I/O) interfaces 6008 ofthe computing system 6000 is configured to be in communication with oneor more external devices 6010 (e.g., a keyboard, a pointing device,and/or a display). In certain examples, the one or more network adapters6012 of the computing system 6000 is configured to communicate with oneor more networks (e.g., a local area network (LAN), a wide area network(WAN), and/or a public network (e.g., the Internet)). In variousexamples, additional hardware and/or software modules are utilized inconnection with the computing system 6000, such as one or moremicro-codes and/or one or more device drivers.

FIG. 4 is a simplified diagram showing a neural network, according tocertain embodiments. This diagram is merely an example, which should notunduly limit the scope of the claims. One of ordinary skill in the artwould recognize many variations, alternatives, and modifications. Insome examples, the neural network 8000 includes an input layer 8002, oneor more hidden layers 8004, and an output layer 8006. For example, theone or more hidden layers 8004 includes L number of neural networklayers, which include a 1^(st) neural network layer, . . . , an i^(th)neural network layer, . . . and an L^(th) neural network layer, where Lis a positive integer and i is an integer that is larger than or equalto 1 and smaller than or equal to L. Although the above has been shownusing a selected group of components for the neural network, there canbe many alternatives, modifications, and variations. For example, someof the components may be expanded and/or combined. Other components maybe inserted to those noted above. Depending upon the embodiment, thearrangement of components may be interchanged with others replaced.

In some examples, some or all processes (e.g., steps) of the method S100are performed by the neural network 8000 (e.g., using the computingsystem 6000). In certain examples, some or all processes (e.g., steps)of the method S100 are performed by the one or more processing units6002 directed by one or more codes that implement the neural network8000. For example, the one or more codes for the neural network 8000 arestored in the one or more system memories 6004 (e.g., one or morenon-transitory computer-readable media), and are readable by thecomputing system 6000 such as by the one or more processing units 6002.

In certain examples, the neural network 8000 is a deep neural network(e.g., a convolutional neural network). In some examples, each neuralnetwork layer of the one or more hidden layers 8004 includes multiplesublayers. As an example, the i^(th) neural network layer includes aconvolutional layer, an activation layer, and a pooling layer. Forexample, the convolutional layer is configured to perform featureextraction on an input (e.g., received by the input layer or from aprevious neural network layer), the activation layer is configured toapply a nonlinear activation function (e.g., a ReLU function) to theoutput of the convolutional layer, and the pooling layer is configuredto compress (e.g., to down-sample, such as by performing max pooling oraverage pooling) the output of the activation layer. As an example, theoutput layer 8006 includes one or more fully connected layers.

In various embodiments, a computer-implemented method for guiding apatient for a medical examination using a medical apparatus includes:receiving an examination protocol for the medical apparatus; determininga reference position based at least in part on the examination protocol;acquiring a first patient position; determining a first deviation metricbased at least in part on comparing the first patient position and thereference position; determining whether the first deviation metric isgreater than a pre-determined deviation threshold; and if the firstdeviation metric is greater than a pre-determined deviation threshold:generating a first positioning guidance based at least in part on thedetermined first deviation metric, the first positioning guidanceincluding guidance for positioning the patient relative to the medicalapparatus. In certain examples, if the first deviation metric is greaterthan a pre-determined deviation threshold, the computer-implementedmethod further includes: acquiring a second patient position;determining a second deviation metric based at least in part oncomparing the second patient position and the reference position; anddetermining whether the second deviation metric is greater than thepre-determined deviation threshold. In some examples, thecomputer-implemented method is implemented according to at least themethod S100 of FIG. 2. In certain examples, the method is implemented byat least the system 10 of FIG. 1.

In some embodiments, determining a first deviation metric based at leastin part on comparing the first patient position and the referenceposition includes: determining a reference vector based at least in parton the determined reference position; determining a first patient vectorbased at least in part on the acquired first patient position;determining a first deviation vector based at least in part on thereference vector and the first patient vector; and determining the firstdeviation metric based at least in part on the first deviation vector.

In some embodiments, determining a first deviation metric based at leastin part on comparing the captured first patient position and thereference position further includes: receiving one or more anatomicalfeatures associated with the medical examination; classifying the firstdeviation vector as irrelevant if the first deviation vector isdetermined based on an anatomical feature that is not included in theone or more anatomical features; and classifying the first deviationvector as relevant if the first deviation vector is determined based onan anatomical feature that is included in the one or more anatomicalfeatures.

In some embodiments, acquiring a first patient position includesacquiring a first patient image and generating the first patientposition based at least in part on the first patient image.

In some embodiments, the computer-implemented method further includes:detecting a foreign object based at least in part on the acquired firstpatient image; and generating a collision avoidance based at least inpart on the foreign object. In certain examples, the collision avoidanceincludes at least one selected from a pause scan instruction, a stopscan instruction, an audio alert, a visual alert, and an overridingre-routing scan path.

In some embodiments, acquiring a first patient image includes acquiringthe first patient image using at least one selected from a RGB sensor, aRGBD sensor, a laser sensor, a FIR sensor, a NIR sensor, and a lidarsensor.

In some embodiments, generating the first patient position based atleast in part on the acquired first patient image includes determiningone or more internal landmarks associated with the acquired firstpatient image, the one or more internal landmarks includes an anatomicalfeature.

In some embodiments, generating the first patient position based atleast in part on the acquired first patient image includes determiningone or more external landmarks associated with the acquired firstpatient image, the one or more external landmarks includes anon-anatomical object.

In some embodiments, generating the first patient position based atleast in part on the acquired first patient image includes generating afirst patient representation. In certain examples, the first patientrepresentation is two-dimensional or three-dimensional. In certainexamples, the patient representation includes at least one selected froman image, a kinematic model, a skeleton model, a surface model, a meshmodel, a point cloud, and a feature list including one or more featureseach having a corresponding coordinate.

In some embodiments, the computer-implemented method further includesgenerating a signal for indicating that the patient is ready for themedical examination using an examination setting if the first deviationmetric is smaller than or equal to the pre-determined deviationthreshold.

In some embodiments, the computer-implemented method further includesdetermining the examination setting, the examination setting includingat least one selected from a scanning path, a scanning angulation, ascanning parameter, a scanning speed, a scanning dose, and patientinformation. In certain examples, determining the examination settingincludes one selected from: determining the examination setting inreal-time based at least in part on one of the reference position andthe first patient position; and selecting the examination setting from aplurality of pre-determined examination settings.

In some embodiments, the computer-implemented method further includespresenting the first positioning guidance continuously or statically.

In some embodiments, generating a first positioning guidance based atleast in part on the determined first deviation metric includesgenerating at least one selected from a visual guidance and an audioguidance.

In some embodiments, generating a visual guidance includes: generatingat least one selected from a visual representation on a display screen,a hologram in the three-dimensional space, a two-dimensional projectionfrom a projector, an augmented reality representation in an augmentedreality eyewear, a virtual reality representation in a virtual realityeyewear, and a lighting cue indicated by a light-emitting device.

In some embodiments, generating an audio guidance includes generating anaudio guidance having an audio volume corresponding to a magnitude ofthe deviation metric.

In some embodiments, generating a visual guidance includes generating anoverlay highlighting the first deviation metric associated with thefirst patient position and the reference position.

In some embodiments, the computer-implemented method further includes:determining a reference accessory position; acquiring a first accessoryposition; determining a first accessory deviation metric based at leastin part on comparing the first accessory position and the referenceaccessory position; determining whether the first accessory deviationmetric is greater than a pre-determined accessory deviation threshold;and if the first accessory deviation metric is greater than apre-determined accessory deviation threshold: generating a firstaccessory positioning guidance based at least in part on the determinedfirst accessory deviation metric, the first accessory positioningguidance including guidance for positioning the patient relative to theaccessory; acquiring a second accessory position; determining a secondaccessory deviation metric based at least in part on comparing thesecond accessory position and the reference accessory position; anddetermining whether the second accessory deviation metric is greaterthan the pre-determined accessory deviation threshold.

In some embodiments, the computer-implemented method further includespresenting the reference position for guiding the positioning of thepatient.

In various embodiments, a system for guiding a patient for a medicalexamination using a medical apparatus includes: a protocol receivingmodule configured to receive an examination protocol for the medicalapparatus; a reference position determining module configured todetermine a reference position based at least in part on the examinationprotocol; a patient position acquiring module configured to acquire afirst patient position; a deviation metric determining module configuredto determine a first deviation metric based at least in part oncomparing the first patient position and the reference position; apositioning guidance module configured to: determine whether the firstdeviation metric is greater than a pre-determined deviation threshold;and if the first deviation metric is greater than a pre-determineddeviation threshold: generate a first positioning guidance based atleast in part on the determined first deviation metric. In certainexamples, the first positioning guidance including guidance forpositioning the patient relative to the medical apparatus. In certainexamples, the patient position acquiring module is further configured toacquire a second patient position. In certain examples, the deviationmetric determining module is further configured to determine a seconddeviation metric based at least in part on comparing the second patientposition and the reference position. In certain examples, thepositioning guidance module is further configured to determine whetherthe second deviation metric is greater than the pre-determined deviationthreshold. In some examples, the system is implemented according to atleast the system 10 of FIG. 1 and/or configured to perform at least themethod S100 of FIG. 2.

In some embodiments, the deviation metric determining module is furtherconfigured to determine a reference vector based at least in part on thedetermined reference position; determine a first patient vector based atleast in part on the acquired first patient position; determine a firstdeviation vector based at least in part on the reference vector and thefirst patient vector; and determine the first deviation metric based atleast in part on the first deviation vector.

In some embodiments, the deviation metric determining module is furtherconfigured to determine one or more anatomical features associated withthe medical examination; classify the first deviation vector asirrelevant if the first deviation vector is determined based on ananatomical feature that is not included in the one or more anatomicalfeatures; and classify the first deviation vector as relevant if thefirst deviation vector is determined based on an anatomical feature thatis included in the one or more anatomical features.

In some embodiments, the patient position acquiring module is furtherconfigured to acquire a first patient image and generate the firstpatient position based at least in part on the first patient image.

In some embodiments, the system further includes a foreign object moduleconfigured to detect a foreign object based at least in part on theacquired first patient image; and generate a collision avoidance basedat least in part on the foreign object. In certain examples, thecollision avoidance includes at least one selected from a pause scaninstruction, a stop scan instruction, an audio alert, a visual alert,and an overriding re-routing scan path.

In some embodiments, the patient position acquiring module is furtherconfigured to acquire the first patient image using at least oneselected from a RGB sensor, a RGBD sensor, a laser sensor, a FIR sensor,a NIR sensor, and a lidar sensor.

In some embodiments, the patient position acquiring module is furtherconfigured to determine one or more internal landmarks associated withthe acquired first patient image, the one or more internal landmarksincludes an anatomical feature.

In some embodiments, the patient position acquiring module is furtherconfigured to determine one or more external landmarks associated withthe acquired first patient image, the one or more external landmarksincludes a non-anatomical object.

In some embodiments, the patient position acquiring module is furtherconfigured to generate a first patient representation. In certainexamples, the first patient representation is two-dimensional orthree-dimensional. In certain examples, the patient representationincludes at least one selected from an image, a kinematic model, askeleton model, a surface model, a mesh model, a point cloud, and afeature list including one or more features each having a correspondingcoordinate.

In some embodiments, the system further includes a signaling moduleconfigured to generate a signal for indicating that the patient is readyfor the medical examination using an examination setting if the firstdeviation metric is smaller than or equal to the pre-determineddeviation threshold.

In some embodiments, the system further includes a settings moduleconfigured to determine the examination setting, the examination settingincluding at least one selected from a scanning path, a scanningangulation, a scanning parameter, a scanning speed, a scanning dose, andpatient information. In certain examples, the settings module is furtherconfigured to determine the examination setting in real-time based atleast in part on one of the reference position and the first patientposition; and/or select the examination setting from a plurality ofpre-determined examination settings.

In some embodiments, the positioning guidance module is furtherconfigured to present the first positioning guidance continuously orstatically.

In some embodiments, the positioning guidance module is furtherconfigured to generate at least one selected from a visual guidance andan audio guidance.

In some embodiments, the positioning guidance module is furtherconfigured to generate at least one selected from a visualrepresentation on a display screen, a hologram in the three-dimensionalspace, a two-dimensional projection from a projector, an augmentedreality representation in an augmented reality eyewear, a virtualreality representation in a virtual reality eyewear, and a lighting cueindicated by a light-emitting device.

In some embodiments, the positioning guidance module is furtherconfigured to generate an audio guidance having an audio volumecorresponding to a magnitude of the deviation metric.

In some embodiments, the positioning guidance module is furtherconfigured to generate an overlay highlighting the first deviationmetric associated with the first patient position and the referenceposition.

In some embodiments, the system further includes an accessory moduleconfigured to: determine a reference accessory position; acquire a firstaccessory position; determine a first accessory deviation metric basedat least in part on comparing the first accessory position and thereference accessory position; determine whether the first accessorydeviation metric is greater than a pre-determined accessory deviationthreshold; and if the first accessory deviation metric is greater than apre-determined accessory deviation threshold: generate a first accessorypositioning guidance based at least in part on the determined firstaccessory deviation metric, the first accessory positioning guidanceincluding guidance for positioning the patient relative to theaccessory; acquire a second accessory position; determine a secondaccessory deviation metric based at least in part on comparing thesecond accessory position and the reference accessory position; anddetermine whether the second accessory deviation metric is greater thanthe pre-determined accessory deviation threshold.

In some embodiments, the positioning guidance module is furtherconfigured to present the reference position for guiding the positioningof the patient.

In various embodiments, a non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe processes including: receiving an examination protocol for themedical apparatus; determining a reference position based at least inpart on the examination protocol; acquiring a first patient position;determining a first deviation metric based at least in part on comparingthe first patient position and the reference position; determiningwhether the first deviation metric is greater than a pre-determineddeviation threshold; and if the first deviation metric is greater than apre-determined deviation threshold: generating a first positioningguidance based at least in part on the determined first deviationmetric, the first positioning guidance including guidance forpositioning the patient relative to the medical apparatus; acquiring asecond patient position; determining a second deviation metric based atleast in part on comparing the second patient position and the referenceposition; and determining whether the second deviation metric is greaterthan the pre-determined deviation threshold. In some examples, thenon-transitory computer-readable medium with instructions stored thereonis implemented according to at least the method S100 of FIG. 2, and/orby the system 10 (e.g., a terminal) of FIG. 1.

In various embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor,performing the process of determining a first deviation metric based atleast in part on comparing the first patient position and the referenceposition includes: determining a reference vector based at least in parton the determined reference position; determining a first patient vectorbased at least in part on the acquired first patient position;determining a first deviation vector based at least in part on thereference vector and the first patient vector; and determining the firstdeviation metric based at least in part on the first deviation vector.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of receiving one or more anatomical features associated withthe medical examination; classifying the first deviation vector asirrelevant if the first deviation vector is determined based on ananatomical feature that is not included in the one or more anatomicalfeatures; and classifying the first deviation vector as relevant if thefirst deviation vector is determined based on an anatomical feature thatis included in the one or more anatomical features.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of acquiring a first patient image and generating the firstpatient position based at least in part on the first patient image.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including detecting a foreign object based atleast in part on the acquired first patient image; and generating acollision avoidance based at least in part on the foreign object. Incertain examples, the collision avoidance includes at least one selectedfrom a pause scan instruction, a stop scan instruction, an audio alert,a visual alert, and an overriding re-routing scan path.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of acquiring the first patient image using at least oneselected from a RGB sensor, a RGBD sensor, a laser sensor, a FIR sensor,a NIR sensor, and a lidar sensor.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of determining one or more internal landmarks associatedwith the acquired first patient image, the one or more internallandmarks includes an anatomical feature.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of determining one or more external landmarks associatedwith the acquired first patient image, the one or more externallandmarks includes a non-anatomical object.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of generating a first patient representation. In certainexamples, the first patient representation is two-dimensional orthree-dimensional. In certain examples, the patient representationincludes at least one selected from an image, a kinematic model, askeleton model, a surface model, a mesh model, a point cloud, and afeature list including one or more features each having a correspondingcoordinate.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including generating a signal for indicating thatthe patient is ready for the medical examination using an examinationsetting if the first deviation metric is smaller than or equal to thepre-determined deviation threshold.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including determining the examination setting, theexamination setting including at least one selected from a scanningpath, a scanning angulation, a scanning parameter, a scanning speed, ascanning dose, and patient information. In certain examples, determiningthe examination setting includes one selected from: determining theexamination setting in real-time based at least in part on one of thereference position and the first patient position; and selecting theexamination setting from a plurality of pre-determined examinationsettings.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including presenting the first positioningguidance continuously or statically.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of generating at least one selected from a visual guidanceand an audio guidance.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of generating at least one selected from a visualrepresentation on a display screen, a hologram in the three-dimensionalspace, a two-dimensional projection from a projector, an augmentedreality representation in an augmented reality eyewear, a virtualreality representation in a virtual reality eyewear, and a lighting cueindicated by a light-emitting device.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of generating an audio guidance includes generating an audioguidance having an audio volume corresponding to a magnitude of thedeviation metric.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, performthe process of generating a visual guidance includes generating anoverlay highlighting the first deviation metric associated with thefirst patient position and the reference position.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including: determining a reference accessoryposition; acquiring a first accessory position; determining a firstaccessory deviation metric based at least in part on comparing the firstaccessory position and the reference accessory position; determiningwhether the first accessory deviation metric is greater than apre-determined accessory deviation threshold; and if the first accessorydeviation metric is greater than a pre-determined accessory deviationthreshold: generating a first accessory positioning guidance based atleast in part on the determined first accessory deviation metric, thefirst accessory positioning guidance including guidance for positioningthe patient relative to the accessory; acquiring a second accessoryposition; determining a second accessory deviation metric based at leastin part on comparing the second accessory position and the referenceaccessory position; and determining whether the second accessorydeviation metric is greater than the pre-determined accessory deviationthreshold.

In some embodiments, the non-transitory computer-readable medium withinstructions stored thereon, that when executed by a processor, furtherperform the processes including presenting the reference position forguiding the positioning of the patient.

For example, some or all components of various embodiments of thepresent invention each are, individually and/or in combination with atleast another component, implemented using one or more softwarecomponents, one or more hardware components, and/or one or morecombinations of software and hardware components. In another example,some or all components of various embodiments of the present inventioneach are, individually and/or in combination with at least anothercomponent, implemented in one or more circuits, such as one or moreanalog circuits and/or one or more digital circuits. In yet anotherexample, while the embodiments described above refer to particularfeatures, the scope of the present invention also includes embodimentshaving different combinations of features and embodiments that do notinclude all of the described features. In yet another example, variousembodiments and/or examples of the present invention can be combined.

Additionally, the methods and systems described herein may beimplemented on many different types of processing devices by programcode including program instructions that are executable by the deviceprocessing subsystem. The software program instructions may includesource code, object code, machine code, or any other stored data that isoperable to cause a processing system to perform the methods andoperations described herein. Other implementations may also be used,however, such as firmware or even appropriately designed hardwareconfigured to perform the methods and systems described herein.

The systems' and methods' data (e.g., associations, mappings, datainput, data output, intermediate data results, final data results, etc.)may be stored and implemented in one or more different types ofcomputer-implemented data stores, such as different types of storagedevices and programming constructs (e.g., RAM, ROM, EEPROM, Flashmemory, flat files, databases, programming data structures, programmingvariables, IF-THEN (or similar type) statement constructs, applicationprogramming interface, etc.). It is noted that data structures describeformats for use in organizing and storing data in databases, programs,memory, or other computer-readable media for use by a computer program.

The systems and methods may be provided on many different types ofcomputer-readable media including computer storage mechanisms (e.g.,CD-ROM, diskette, RAM, flash memory, computer's hard drive, DVD, etc.)that contain instructions (e.g., software) for use in execution by aprocessor to perform the methods' operations and implement the systemsdescribed herein. The computer components, software modules, functions,data stores and data structures described herein may be connecteddirectly or indirectly to each other in order to allow the flow of dataneeded for their operations. It is also noted that a module or processorincludes a unit of code that performs a software operation and can beimplemented for example as a subroutine unit of code, or as a softwarefunction unit of code, or as an object (as in an object-orientedparadigm), or as an applet, or in a computer script language, or asanother type of computer code. The software components and/orfunctionality may be located on a single computer or distributed acrossmultiple computers depending upon the situation at hand.

The computing system can include client devices and servers. A clientdevice and server are generally remote from each other and typicallyinteract through a communication network. The relationship of clientdevice and server arises by virtue of computer programs running on therespective computers and having a client device-server relationship toeach other.

This specification contains many specifics for particular embodiments.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations, one or more features from a combination can in some casesbe removed from the combination, and a combination may, for example, bedirected to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Although specific embodiments of the present invention have beendescribed, it will be understood by those of skill in the art that thereare other embodiments that are equivalent to the described embodiments.Accordingly, it is to be understood that the invention is not to belimited by the specific illustrated embodiments.

What is claimed is:
 1. A computer-implemented method for guiding apatient for a medical examination using a medical apparatus, the methodcomprising: receiving an examination protocol for the medical apparatus;determining, by one or more processors, a reference position based atleast in part on the examination protocol; acquiring a patient position;determining, by the one or more processors, a deviation metric based atleast in part on comparing the patient position and the referenceposition; determining, by the one or more processors, whether thedeviation metric is greater than a pre-determined deviation threshold;and if the deviation metric is greater than the pre-determined deviationthreshold: generating a positioning guidance based at least in part onthe determined deviation metric, the positioning guidance includingguidance for positioning the patient relative to the medical apparatus;wherein the determining a deviation metric based at least in part oncomparing the patient position and the reference position includes:determining a reference vector based at least in part on the determinedreference position; determining a patient vector based at least in parton the acquired patient position; determining a deviation vector basedat least in part on the reference vector and the patient vector; anddetermining the deviation metric based at least in part on the deviationvector.
 2. The computer-implemented method of claim 1, wherein thedetermining a deviation metric based at least in part on comparing thecaptured patient position and the reference position further includes:receiving one or more anatomical features associated with the medicalexamination; classifying the deviation vector as irrelevant if thedeviation vector is determined based on an anatomical feature that isnot included in the one or more anatomical features; and classifying thedeviation vector as relevant if the deviation vector is determined basedon an anatomical feature that is included in the one or more anatomicalfeatures.
 3. The computer-implemented method of claim 1, wherein theacquiring a patient position includes: acquiring a patient image; andgenerating the patient position based at least in part on the patientimage.
 4. The computer-implemented method of claim 3, furthercomprising: detecting a foreign object based at least in part on theacquired patient image; and generating a collision avoidance based atleast in part on the foreign object; wherein the collision avoidanceincludes one selected from a pause scan instruction, a stop scaninstruction, an audio alert, a visual alert, and an overridingre-routing scan path.
 5. The computer-implemented method of claim 3,wherein the acquiring a patient image includes: acquiring the patientimage using at least one selected from a RGB sensor, a RGBD sensor, alaser sensor, a far infrared (“FIR”) sensor, a near infrared (“NIR”)sensor, and a lidar sensor.
 6. The computer-implemented method of claim3, wherein the generating the patient position based at least in part onthe acquired patient image includes: determining one or more internallandmarks associated with the acquired patient image, the one or moreinternal landmarks includes an anatomical feature.
 7. Thecomputer-implemented method of claim 3, wherein the generating thepatient position based at least in part on the acquired patient imageincludes: determining one or more external landmarks associated with theacquired patient image, the one or more external landmarks includes anon-anatomical object.
 8. The computer-implemented method of claim 3,wherein the generating the patient position based at least in part onthe acquired patient image includes: generating a patientrepresentation; wherein the patient representation is two-dimensional orthree-dimensional; wherein the patient representation includes oneselected from an image, a kinematic model, a skeleton model, a surfacemodel, a mesh model, a point cloud, and a feature list including one ormore features each having a corresponding coordinate.
 9. Thecomputer-implemented method of claim 1, further comprising: generating asignal for indicating that the patient is ready for the medicalexamination using an examination setting if the deviation metric issmaller than or equal to the pre-determined deviation threshold.
 10. Thecomputer-implemented method of claim 9, further comprising: determiningthe examination setting, the examination setting including one selectedfrom a scanning path, a scanning angulation, a scanning parameter, ascanning speed, a scanning dose, and patient information; whereindetermining the examination setting includes one selected from:determining the examination setting in real-time based at least in parton one of the reference position and the patient position; and selectingthe examination setting from a plurality of pre-determined examinationsettings.
 11. The computer-implemented method of claim 1, furthercomprising: presenting the positioning guidance continuously orstatically.
 12. The computer-implemented method of claim 11, wherein thegenerating a visual guidance includes: generating at least one selectedfrom a visual representation on a display screen, a hologram in thethree-dimensional space, a two-dimensional projection from a projector,an augmented reality representation in an augmented reality eyewear, avirtual reality representation in a virtual reality eyewear, and alighting cue indicated by a light-emitting device.
 13. Thecomputer-implemented method of claim 11, wherein the generating an audioguidance includes: generating an audio guidance having an audio volumecorresponding to a magnitude of the deviation metric.
 14. Thecomputer-implemented method of claim 11, wherein the generating a visualguidance includes: generating an overlay highlighting the deviationmetric associated with the patient position and the reference position.15. The computer-implemented method of claim 1, wherein the generating apositioning guidance based at least in part on the determined deviationmetric includes: generating at least one selected from a visual guidanceand an audio guidance.
 16. The computer-implemented method of claim 1,further comprising: determining a reference accessory position;acquiring an accessory position; determining an accessory deviationmetric based at least in part on comparing the accessory position andthe reference accessory position; determining whether the accessorydeviation metric is greater than a pre-determined accessory deviationthreshold; and if the accessory deviation metric is greater than thepre-determined accessory deviation threshold: generating an accessorypositioning guidance based at least in part on the determined accessorydeviation metric, the accessory positioning guidance including guidancefor positioning the patient relative to the accessory.
 17. Thecomputer-implemented method of claim 1, further comprising: presentingthe reference position for guiding the positioning of the patient.
 18. Asystem for guiding a patient for a medical examination using a medicalapparatus, the system comprising: a protocol receiving moduleimplemented on one or more processors and configured to receive anexamination protocol for the medical apparatus; a reference positiondetermining module implemented on the one or more processors andconfigured to determine a reference position based at least in part onthe examination protocol; a patient position acquiring moduleimplemented on the one or more processors and configured to acquire apatient position; a deviation metric determining module implemented onthe one or more processors and configured to determine a deviationmetric based at least in part on comparing the patient position and thereference position; a positioning guidance module implemented on the oneor more processors and configured to: determine whether the deviationmetric is greater than a pre-determined deviation threshold; and if thedeviation metric is greater than a pre-determined deviation threshold:generate a positioning guidance based at least in part on the determineddeviation metric, the positioning guidance including guidance forpositioning the patient relative to the medical apparatus; wherein thedeviation metric determining module is further configured to: determinea reference vector based at least in part on the determined referenceposition; determine a patient vector based at least in part on theacquired patient position; determine a deviation vector based at leastin part on the reference vector and the patient vector; and determinethe deviation metric based at least in part on the deviation vector. 19.A non-transitory computer-readable medium with instructions storedthereon, that when executed by a processor, perform the processescomprising: receiving an examination protocol for the medical apparatus;determining a reference position based at least in part on theexamination protocol; acquiring a patient position; determining adeviation metric based at least in part on comparing the patientposition and the reference position; determining whether the deviationmetric is greater than a pre-determined deviation threshold; and if thedeviation metric is greater than the pre-determined deviation threshold:generating a positioning guidance based at least in part on thedetermined deviation metric, the positioning guidance including guidancefor positioning the patient relative to the medical apparatus; whereinthe determining a deviation metric based at least in part on comparingthe patient position and the reference position includes: determining areference vector based at least in part on the determined referenceposition; determining a patient vector based at least in part on theacquired patient position; determining a deviation vector based at leastin part on the reference vector and the patient vector; and determiningthe deviation metric based at least in part on the deviation vector.